source: sasview/sansmodels/src/sans/models/BaseComponent.py @ 7b0fd65

ESS_GUIESS_GUI_DocsESS_GUI_batch_fittingESS_GUI_bumps_abstractionESS_GUI_iss1116ESS_GUI_iss879ESS_GUI_iss959ESS_GUI_openclESS_GUI_orderingESS_GUI_sync_sascalccostrafo411magnetic_scattrelease-4.1.1release-4.1.2release-4.2.2release_4.0.1ticket-1009ticket-1094-headlessticket-1242-2d-resolutionticket-1243ticket-1249ticket885unittest-saveload
Last change on this file since 7b0fd65 was c9636f7, checked in by Gervaise Alina <gervyh@…>, 16 years ago

model multiplication and testing

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File size: 5.1 KB
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1#!/usr/bin/env python
2"""
3    Provide base functionality for all model components
4"""
5
6# imports   
7import copy
8#TO DO: that about a way to make the parameter
9#is self return if it is fittable or not 
10
11class BaseComponent:
12    """
13        Basic model component
14       
15        Since version 0.5.0, basic operations are no longer supported.
16    """
17
18    def __init__(self):
19        """ Initialization"""
20       
21        ## Name of the model
22        self.name   = "BaseComponent"
23       
24        ## Parameters to be accessed by client
25        self.params = {}
26        self.details = {}
27        ## Dictionary used to store the dispersity/averaging
28        #  parameters of dispersed/averaged parameters.
29        self.dispersion = {}
30        # string containing information about the model such as the equation
31        #of the given model, exception or possible use
32        self.description=''
33        #list of parameter that can be fitted
34        self.fixed= []
35           
36    def __str__(self):
37        """
38            @return: string representation
39        """
40        return self.name
41   
42    def is_fittable(self, par_name):
43        """
44            Check if a given parameter is fittable or not
45            @param par_name: the parameter name to check
46        """
47        return par_name.lower() in self.fixed
48        #For the future
49        #return self.params[str(par_name)].is_fittable()
50   
51    def run(self, x): return NotImplemented
52    def runXY(self, x): return NotImplemented 
53   
54    def clone(self):
55        """ Returns a new object identical to the current object """
56        obj = copy.deepcopy(self)
57        return self._clone(obj)
58   
59    def _clone(self, obj):
60        """
61            Internal utility function to copy the internal
62            data members to a fresh copy.
63        """
64        obj.params     = copy.deepcopy(self.params)
65        obj.details    = copy.deepcopy(self.details)
66        obj.dispersion = copy.deepcopy(self.dispersion)
67        return obj
68
69    def setParam(self, name, value):
70        """
71            Set the value of a model parameter
72       
73            @param name: name of the parameter
74            @param value: value of the parameter
75        """
76        # Look for dispersion parameters
77        toks = name.split('.')
78        if len(toks)==2:
79            for item in self.dispersion.keys():
80                if item.lower()==toks[0].lower():
81                    for par in self.dispersion[item]:
82                        if par.lower() == toks[1].lower():
83                            self.dispersion[item][par] = value
84                            return
85        else:
86            # Look for standard parameter
87            for item in self.params.keys():
88                if item.lower()==name.lower():
89                    self.params[item] = value
90                    return
91           
92        raise ValueError, "Model does not contain parameter %s" % name
93       
94    def getParam(self, name):
95        """
96            Set the value of a model parameter
97
98            @param name: name of the parameter
99        """
100        # Look for dispersion parameters
101        toks = name.split('.')
102        if len(toks)==2:
103            for item in self.dispersion.keys():
104                if item.lower()==toks[0].lower():
105                    for par in self.dispersion[item]:
106                        if par.lower() == toks[1].lower():
107                            return self.dispersion[item][par]
108        else:
109            # Look for standard parameter
110            for item in self.params.keys():
111                if item.lower()==name.lower():
112                    return self.params[item]
113           
114        raise ValueError, "Model does not contain parameter %s" % name
115     
116    def getParamList(self):
117        """
118            Return a list of all available parameters for the model
119        """ 
120        list = self.params.keys()
121        # WARNING: Extending the list with the dispersion parameters
122        list.extend(self.getDispParamList())
123        return list
124   
125    def getDispParamList(self):
126        """
127            Return a list of all available parameters for the model
128        """ 
129        list = []
130       
131        for item in self.dispersion.keys():
132            for p in self.dispersion[item].keys():
133                if p not in ['type']:
134                    list.append('%s.%s' % (item.lower(), p.lower()))
135                   
136        return list
137   
138    # Old-style methods that are no longer used
139    def setParamWithToken(self, name, value, token, member): return NotImplemented
140    def getParamWithToken(self, name, token, member): return NotImplemented
141    def getParamListWithToken(self, token, member): return NotImplemented
142    def __add__(self, other): raise ValueError, "Model operation are no longer supported"
143    def __sub__(self, other): raise ValueError, "Model operation are no longer supported"
144    def __mul__(self, other): raise ValueError, "Model operation are no longer supported"
145    def __div__(self, other): raise ValueError, "Model operation are no longer supported"
146       
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